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library(tidyverse)
library(ggpubr)
data <- read_csv("../csv/repeat_investigation.csv")
studies_data <- read_csv("../csv/donors_list.csv") %>%
group_by(study_id) %>%
summarise(
count = n()
)
tbl <- data %>%
na_if("NULL") %>%
select(
donor_id,
visit_year,
study_id,
visit_type_hai,
vaccine_resp
) %>%
group_by(
donor_id, study_id, visit_year
) %>%
summarise(
type = visit_type_hai,
response = vaccine_resp
)
response_vec <- tbl %>%
group_map(
~ {
if (any(!is.na(.$response))) {
rep(TRUE, nrow(.))
} else {
rep(FALSE, nrow(.))
}
}
)
tbl_pre <- tbl %>%
ungroup() %>%
mutate(response_recorded = unlist(response_vec)) %>%
filter(type == "pre" | type == "single") %>%
group_by(
donor_id, study_id
) %>%
summarise(
count = n(),
year = visit_year,
type = type,
response = response,
recorded = response_recorded
)
tbl_pre
plt <- tbl_pre %>%
ggplot(aes(count, fill = factor(recorded, labels=c("No (for various reasons)", "Yes")))) +
geom_bar() +
facet_wrap(~ factor(study_id, labels = c(
paste("SLVP015\nn=(", as.numeric(studies_data[studies_data$study_id == 15,][2]), ")"),
paste("SLVP017\nn=(", as.numeric(studies_data[studies_data$study_id == 17,][2]), ")"),
paste("SLVP018\nn=(", as.numeric(studies_data[studies_data$study_id == 18,][2]), ")"),
paste("SLVP021\nn=(", as.numeric(studies_data[studies_data$study_id == 21,][2]), ")"),
paste("SLVP024\nn=(", as.numeric(studies_data[studies_data$study_id == 24,][2]), ")"),
paste("SLVP028\nn=(", as.numeric(studies_data[studies_data$study_id == 28,][2]), ")"),
paste("SLVP029\nn=(", as.numeric(studies_data[studies_data$study_id == 29,][2]), ")"),
paste("SLVP030\nn=(", as.numeric(studies_data[studies_data$study_id == 30,][2]), ")")
))) +
labs(x="Seasons a donor visited", y = "Visits by donors with same amount of total seasons", fill = "Response classification available") +
theme_pubr() +
scale_x_continuous(breaks = scales::pretty_breaks(n = 8))
plt
ggsave("../images/repeat_visits_per_study.png", plt, width = 2*15, height = 25, dpi=300, units = "cm")
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